Kumar, Sat and Sekhar, M and Bandyopadhyay, Sanjoy (2009) Assimilation of remote sensing and hydrological data using adaptive filtering techniques for watershed modelling. In: Current Science, 97 (8). pp. 1196-1202.
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The knowledge of hydrological variables (e. g. soil moisture, evapotranspiration) are of pronounced importance in various applications including flood control, agricultural production and effective water resources management. These applications require the accurate prediction of hydrological variables spatially and temporally in watershed/basin. Though hydrological models can simulate these variables at desired resolution (spatial and temporal), often they are validated against the variables, which are either sparse in resolution (e. g. soil moisture) or averaged over large regions (e. g. runoff). A combination of the distributed hydrological model (DHM) and remote sensing (RS) has the potential to improve resolution. Data assimilation schemes can optimally combine DHM and RS. Retrieval of hydrological variables (e. g. soil moisture) from remote sensing and assimilating it in hydrological model requires validation of algorithms using field studies. Here we present a review of methodologies developed to assimilate RS in DHM and demonstrate the application for soil moisture in a small experimental watershed in south India.
|Item Type:||Journal Article|
|Additional Information:||Copyright for this article belongs to Indian Academy of Sciences.|
|Keywords:||Data assimilation; hydrological model; remote sensing; soil moisture|
|Department/Centre:||Division of Mechanical Sciences > Civil Engineering|
|Date Deposited:||01 Dec 2009 06:10|
|Last Modified:||19 Sep 2010 05:53|
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